PhD in In-Memory Computing Based on FeFET for Low-Power Embedded AI

This doctoral position focuses on in-memory computing architectures utilizing ferroelectric field-effect transistors (FeFET) to support low-power embedded artificial intelligence applications. The project aims to address energy constraints in modern edge computing through innovative hardware design and algorithm-hardware co-design. The successful candidate will conduct experimental and theoretical research within a specialized laboratory environment in France. Responsibilities include designing device-level configurations, implementing circuit simulations, and publishing findings in academic venues.

• Design and model FeFET-based in-memory computing architectures for low-power artificial intelligence applications
• Perform electrical characterization and circuit simulations to evaluate performance and energy efficiency
• Collaborate with research team members on hardware-software co-design strategies
• Draft scientific manuscripts and present research findings at international conferences and in peer-reviewed journals
• Contribute to ongoing laboratory projects and engage with academic and industrial partners